Search NASA⌕ Search

SEARCH · Search NASA

Results for “differentiable programming”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Interferon-Stimulated Response to Virus Infection, Processed Experimental Dataset Catalog

Human Interferon (IFN) alpha, beta, and gamma participate in the body's natural immune response to lethal virus infection and disease.The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013 - 2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Human Interferon (IFN), interferon alpha (IFNα), interferon beta (IFNβ), and/or interferon gamma (IFNγ) stimulated response to an experimental virus infection treatment study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Photofission Validation Measurements for Active Interrogation Standards

Executive Summary PNNL has been developing technical standards for the detection of special nuclear material (SNM) in cargo containers using active interrogation approaches. Since the use of kilogram-scale quantities of SNM is impractical for standards testing, the work focused on designing surrogates that provided similar signature as the SNM. There are many active interrogation approaches to detect SNM; the standards development considered photofission, differential die-away and nuclear resonance fluorescence. Of these approaches, photofission currently carries the most interest. However, uncertainties in the photofission cross sections are as large as 50%, so that validation measurements are necessary to provide confidence that the surrogate will perform similarly to the SNM. This document describes approaches for conducting those validation measurements as well as provides a rough order-of-magnitude cost estimate for performing them. Photofission provides many observables for the detection of SNM. The standards development considered prompt neutrons, delayed neutrons and delayed gamma rays as possible detected particles. The surrogates, which consist primarily of depleted uranium (DU), were designed to reproduce the strength of these particles for a targeted quantity of 2 kg of HEU. Different surrogates are required for different measurement approaches because of the difference in cross section between 235 U and 238 U. For the standards validations, the relative strength of the detected particles for HEU and DU must be measured. To avoid measurements with kilogram-sized SNM, the validation approach is focused on two comparisons. In the first comparison, the relative rates for approximately 10 g samples of DU and HEU will be measured. This comparison will provide the basis for validating the relative strength of the detected particles for HEU and DU. In the second comparison, the relative rates for the approximately 10 g and 1 kg sample of DU will be measured. This comparison will enable the validation of secondary processes that occur after photofission that impact the measurement for kilogram-scale samples. For instance, for 2 kg of HEU, as much as 50% of the fission induced in the sample is induced from fission neutrons generated through photofission. There is a limited range of facilities in the U.S. that have both the necessary accelerator capability and the ability and willingness to handle SNM. Two such facilities, the Idaho Accelerator Center at Idaho State University and the Nuclear Engineering Program at the University of Michigan, have both expressed an interest in participating in such measurements. Both would need to amend their licensing to handle the 10 g of HEU proposed for these measurements. The rough order-of-magnitude cost estimate for all three validation measurements is $1.1M, spread over three years. Each of the three measurements could be performed separately, at approximately one-third of that cost. There are a number of critical assumptions in these cost estimate that will need to be confirmed before a more reliable cost estimate can be established. PNNL will manage the effort to ensure that the overall objective of the validation measurements can be achieved and will fabricate the 10 g samples of HEU and DU. Most the labor for the measurements will be provided by two collaborating universities as research opportunities for students. The successful completion of these validation measurements will reduce the uncertainties in the proposed standards from about 50% to 5%. The measurements would also provide some much-needed nuclear data on photofission.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

On a measurement approach to support evaluation of thermal scattering law data

Inelastic thermal neutron scattering in materials that act as neutron moderators, reflectors, and filters results in shaping the neutron spectrum at low energies. This phenomenon is described using differential scattering cross sections calculated from three components including the bound atom (i.e., nuclear) scattering cross section of the neutron, the ratio of the outgoing and incoming neutron energy, and the thermal scattering law (TSL), i.e., S(α,β), where α and β represent dimensionless momentum and energy exchange variables, respectively. To date, no TSL libraries are generated using measured data. However, valuable information may be derived from measurements and “targeted” experiments that can validate TSL data and the related inelastic scattering cross sections. As a demonstration, a suite of coordinated measurements and experiments is described that was designed and used to support the evaluation of the TSL for “nuclear” graphite. This experimental suite includes neutron powder diffraction (for structure analysis), positron annihilation (for nano porosity assessment), inelastic neutron scattering measurements using a chopper spectrometer, transmission experiments using neutrons with energy below the Bragg cutoff thereby accessing the total (inelastic) cross section, and a slowing-downtime experiment to observe the developing neutron spectrum in the material. We find that this experimental suite was key to understanding the difference in TSL between “nuclear” and “ideal” graphite and for the inclusion of “nuclear” graphite in the ENDF/B-VIII.0 nuclear data library release.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

SU-E-T-679: Retrospective Analysis of the Sensitivity of Planar Dose Measurements To Gamma Analysis Criteria

Purpose: IMRT QA using planar dose measurements is still a widely used method for checking the accuracy of treatment plans. A pass/fail judgment is made using gamma analysis based on a single endpoint. Using more stringent criteria is a way to increase the sensitivity to planning and delivery errors. Before such implementation, it is necessary to understand how the sensitivity to different gamma criteria settings affects gamma passing rates (GPR). Methods: 752 IMRT QA measurements were re-analyzed with varying distance to agreement (DTA) and dose difference (DD) percentages using a Matlab program. Other quantifying information such as the mean dose difference in the treatment target (defined as points that are greater than 80% of maximal dose) were stored in a relational database for retrospective analysis. Results: The average and standard deviation of GPR (%) fell from 99.84 ± (0.43) to 89.61 ± (6.08) when restricting DD from 5 − 1% respectively, as compared to a drop from 99.15 ± (1.19) to 95.00 ± (4.43), when restricting the DTA from 5 − 1 mm respectively. The mean dose difference (%) in the treatment target between measured and calculated dose was −1.96 ± (0. 83), −0.09 ± (0.98), and 1.44 ± (0. 86) for each of our institution’s three matched linear accelerators (LINAC 1, 2, and 3 respectively). For plans that are approximately 2.7 sigma below the mean GPR, an average of 78.4% of those plans were measured on LINAC 1 or 3, while only 48% of the total plans were run on those machines. Conclusion: The data demonstrates that when restricting gamma criterion, such as the DD, the greatest indicator of reduced GPR in our institution is which matched LINAC the plan was measured on. While small, these differences manifest themselves to levels comparable to other treatment related differences and possibly confound the gamma analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to West Nile Virus Infection, Processed Experimental Dataset Catalog

West Nile virus (WNV) is classified as a Category B priority pathogen (mosquito-borne Flavivirus) by the National Institute of Allergy and Infectious Diseases (NIAID), and are known to cause severe infections in humans where lethal host-associated mechanisms are not clearly defined. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013 - 2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding a specific West Nile virus [NCBITAXON:11082] (WNV-NY99 382) experimental infection study. Host sample types include cerebellum ["CB", BTO:0000232], cortical neurons ["CN", BTO:0004102], cortex ["CT", BTO:0000233], dendritic cells ["DC", BTO:0002042], granule cell neurons ["GCN", BTO:0003393], lymph node ["LN", BTO:0000784], and serum ["SE", BTO:0001239] from mouse (Mus musculus) tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Exploring the interplay of resilience and energy consumption for a task-based partial differential equations preconditioner

Here, we discuss algorithm-based resilience to silent data corruptions (SDCs) in a task-based domain-decomposition preconditioner for partial differential equations (PDEs). The algorithm exploits a reformulation of the PDE as a sampling problem, followed by a solution update through data manipulation that is resilient to SDCs. The implementation is based on a server-client model where all state information is held by the servers, while clients are designed solely as computational units. Scalability tests run up to ~51K cores show a parallel efficiency greater than 90%. We use a 2D elliptic PDE and a fault model based on random single and double bit-flip to demonstrate the resilience of the application to synthetically injected SDC. We discuss two fault scenarios: one based on the corruption of all data of a target task, and the other involving the corruption of a single data point. We show that for our application, given the test problem considered, a four-fold increase in the number of faults only yields a 2% change in the overhead to overcome their presence, from 7% to 9%. We then discuss potential savings in energy consumption via dynamic voltage/frequency scaling, and its interplay with fault-rates, and application overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

PNNL DataHub Project: Omics Lethal Human Viruses Project Profiling of the Host Response to Ebola Virus Infection, Processed Experimental Dataset Catalog

Ebola virus (EBOV) is high risk biological agent, classified as a Category A priority pathogen (Flaviviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), known to cause hemorrhagic fever with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific Ebola virus [NCBITAXON:186536] (Zaire/Makona or Zaire/Mayinga) experimental infection study. Human host samples types include peripheral blood mononuclear cells isolated from blood plasma ["PBMC", BTO:0001025], human hepatoma carcinoma cells ["HUH", BTO:0001950], human umbilical vein endothelial cells ["HUVEC", BTO:0001949], immortalized human hepatocyte cells ["IHH", BTO:0006147], and human histiocytic lymphoma cells ["U937", BTO:0001412].

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog

Middle East Respiratory Syndrome coronavirus (MERS-CoV) is classified as a Category C priority pathogen (Coronaviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV [NCBITAXON:1335626] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750], human bronchial epithelial cells ["Calu-3 clone 2B4"; BTO:0002022], primary human fibroblasts ["FB"; BTO:0000452], primary human airway epithelial cells ["HAE"; BTO:0005571], human microvascular endothelial cells ["HMVE"; BTO:0003123], and whole mouse lung [BTO:0000763] tissue collections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Crosscutting Recombination Metrology for Expediting VOC Engineering

Work carried out under this grant addressed the need for improved materials and device characterization of solar cell designs. This experimental program aimed to develop joint electrical and optical studies of solar cells based on the group-II-VI semiconductor CdTe and the chalcogenide semiconductor Cu(InGa)Se 2 . Electrical measurements focused on temperature (T) and illumination intensity (I) dependence of the open-circuit voltage (VOC), a quantity that plays an important role in conversion efficiency. The VOC depends on temperature and illumination intensity through the energy gap and positions of the quasiFermi levels (QFLs). Optical measurements exploited the illumination and temperature dependence of absolute photoluminescence (PL) intensity (PL-I), a quantity that also depends on the QFL positions. The QFL splitting is a quantity that also depends on recombination rates within the solar cell, including radiative and non-radiative processes. Other factors affect the electrical and optical properties. These include band offsets at both the front and back interfaces of the device active region where electrical contacts are formed. Understanding, locating, and quantifying the recombination properties of the solar cells was the principal goal of this research. Custom simulations were developed to solve continuity and Poisson equations selfconsistently to obtain free-electron and free-hole concentrations. The measurements of temperature and intensity dependent VOC and PL-I allowed the extraction of a number of physical parameters including the conduction band offset, the shunt constant, and the effective capture coefficient for recombination centers, both within the absorber and at the absorber-buffer interface. In addition, the back-contact barrier height is determined from electrical properties. Each of these is discussed in the report. The illumination intensity dependence of VOC and PL-I do not overlap in experiments primarily because PL is not observed in the low-intensity regime where VOC is studied. Absolute PL-I measurements enabled development of an approach directly comparing it with VOC. This in turn allowed development of a simulation capability that would consistently use both measurements, as functions of T and I, for producing a minimization scheme using a differential evolution algorithm. The approach was applied to both CdTe and Cu(InGa)Se 2 solar cells each prepared under various conditions. Shunt conductivity, QFL splitting, recombination were measured. Also extensively studied are current-voltage and frequency-dependent capacitance voltage. Work completed under this grant included studies of magnesium zinc oxide (MZO) buffered CdTe solar cells including the effects of hydroiodic acid (HI) treatment. From these studies the recombination rates were quantified at the buffer/absorber (front) interface. The effect of back-contact barrier height was investigated. CdTe solar cells were prepared with CdSe and CdS buffer layers. Lower grain-boundary potential fluctuation, higher back-contact barrier height, and greater bulk recombination were observed in early devices with CdSe buffer layer. Investigations were also carried out into CdS/Cu(InGa)Se 2 solar cells. A metal-insulatorsemiconductor capacitance-voltage technique was developed to extract recombinationrelevant properties of the absorber interface. From this work the density of interface states D it , their capture cross-section σ, fixed charge at the interface Q f , and surface recombination velocity were all extracted.

14 SOLAR ENERGY↗
DOE OSTI2022

MOOSE Reactor Module Meshing Enhancements to Support Reactor Physics Analysis

The U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program develops an integrated suite of advanced reactor physics tools built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Each code generally requires an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The meshing process is often burdensome for the complex geometries present in reactors due to lack of easy-to-use, open-source meshing tools. To address the bottleneck associated with meshing complex geometries found in nuclear reactors, NEAMS initiated the development of the MOOSE Reactor Module starting in FY21. The Reactor Module builds off the existing MOOSE Mesh System to include targeted meshing capabilities such as the ability to generate hexagonal pin cells, assemblies with ducts, rotating control drums, cores, peripheral zones around a core, as well as the automatic labeling (“reporting IDs”) of pin, assembly, and planar zones to simplify post-processing of results. As a Physics Module in MOOSE, the Reactor Module is open-source, available with any MOOSE installation, directly compatible with MOOSE-based tools, and can be invoked from MOOSEbased applications to generate meshes. Functionality from the Reactor Module has been applied to several advanced reactor concepts to demonstrate user workflow improvements and accuracy. The primary objective of the Reactor Module is to improve useability of MOOSEbased tools by streamlining mesh generation and output inspection processes. During FY22, the functionality of the Reactor Module (and accompanying Mesh System) has been expanded based on user needs. First, the Reactor Geometry Mesh Builder capability developed primarily in FY21 has been refactored and merged to the public MOOSE repository. This capability wraps underlying Reactor Module mesh generators into a “Pin – Assembly – Core” workflow appropriate for conventional Cartesian and hexagonal geometries, and notably assigns material IDs during mesh generation stage and generates only the minimal number of blocks needed in order to reduce computational burden. Biasing and boundary layer options have been added to the base mesh generators as required by thermal hydraulics solvers. The reporting ID functionality has been expanded to differentiate ring-wise and azimuthal sectors within a pin for use with depletion algorithms, and VectorPostProcessor and Reporter objects are now available to integrate solution variables across zones based on ID combinations. Functionality to trim hexagonal meshes along the center or periphery has been developed so users may leverage symmetry and reflective boundary conditions to reduce the mesh size. A flexible and powerful tool to fill the space between two sidesets has been introduced to the framework and can be used for transition layers such as stitching two assemblies together with different numbers of pins, or for complex geometries which do not follow conventional Cartesian/hexagonal patterns. Finally, additional verification problems were performed with NEAMS physics tools in complement with existing NEAMS work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Measurements of Neutron Scattering from a Copper Sample Using a Quasi-Differential Method in the Region from 2 keV to 20 MeV

Neutron scattering from a copper sample was measured at Rensselaer Polytechnic Institute utilizing the quasi-differential method. The measurement spanned the energy range from 0.5 to 20 MeV using the high-energy scattering system and from 2 keV to 0.5 MeV using the new mid-energy scattering system. Copper was selected as a material of interest to measure due to large discrepancies between experiments and simulations of the Zeus benchmark. The Zeus benchmark consists of a copper reflected highly enriched uranium system, and the angular distribution of copper scattering was thought to potentially be the cause of the discrepancy. The copper measurements found differences in the scattering response particularly in the incident energy region from 1 to 2 MeV for the high-energy measurement and from 2 to 4 keV in the mid-energy system. These differences are particularly noticeable at angles near 90 deg in the high-energy system and back angles in the mid-energy system. Additionally, for ENDF/B-VIII.0 there is a large discrepancy at the forward angle in the energy range around 0.5 MeV. For these reasons, a new evaluation of copper scattering utilizing these results is recommended and perhaps could help to improve the agreement with the Zeus benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Physics and Criticality Safety Applications

Many new reactor designs, such as advanced reactors and micro reactors, have materials that lack nuclear data validation. This is also true for many other applications in criticality safety and global security. Both differential and integral experiments are needed to validate cross-section data. Without this, a user cannot have confidence in the predicted results of a radiation-transport code. This work describes an approach called ARCHIMEDES (Application Relevant Critical/Subcritical HEU/Pu-based Integral Measurements for Enhancing Data and Evaluating Sensitivities) to design new criticality experiments that have similar k eff cross-section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. Recently, there has been a great deal of interest in the reactor physics community on advanced reactors, micro reactors, and accelerator driven systems (ADS). This work will apply the described method to specific examples in this area. The focus of this work will be on the sensitivity study and gap analysis, while future work will include experiment design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Neutron Leakage Spectra of the EUCLID Experiment [Abstract]

Integral experiments with sub-critical and critical configurations of special nuclear material are performed in support of nuclear data validation and adjustment. Different nuclear data evaluations may have different values for individual cross sections due to uncertainties in (or lack of) differential experiments, but compensating errors in these data sets can lead to the same k eff results for one application while vastly different for another application. One example of this is 239 Pu, where both ENDF/B-VIII.0 and JEFF-3.3 correctly compute k eff of the Jezebel critical assembly, but the individual contributions from each reaction are vastly different. To help resolve this specific case, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project used machine learning to design a set of experiments to help resolve the compensating errors in 239 Pu. A total of six responses were measured during the experimental campaign, which constrain the data in ways that k eff alone cannot and will be used for adjustment of the nuclear data. One of these responses is the neutron leakage spectrum, which recent work has shown to be useful for constraining the prompt fission neutron spectrum and inelastic scattering. The neutron leakage spectra were measured utilizing a 3 in. right cylinder EJ-301D detector. The measured signal in the detector was deconvoluted using spectrum unfolding techniques, which are presented and compared to simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Natural and Engineered Features Supporting Environmental Performance of Idaho National Laboratory’s Remote-Handled Low-Level Waste Disposal Facility

The Idaho National Laboratory’s (INL’s) Remote-Handled Low-Level Waste (RH LLW) Disposal Facility has been designed and constructed to receive waste generated at the INL site in support of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) and Naval Reactors (NR) missions. The facility has been designed to receive legacy RH LLW currently in storage at INL facilities and new waste generated by nuclear research programs. RH LLW to be received at the facility is solid waste consisting of surface contaminated debris; ion exchange resins used to purify cooling and canal water; activated metals generated during reactor core change outs and Naval spent fuel management; and nuclear Research & Development. Disposal of INL's RH LLW poses unique disposal challenges due to high radiation levels (contact rates up to 600 Sv/hr [60,000 Rem/hr]) that require remote handling and adequate shielding for transportation and disposal. The facility has been designed to meet the requirements of DOE Order 435.1 [1], including the all-pathways dose, air pathway dose, inadvertent intruder doses, and radon emissions limits. This paper presents an overview of natural and engineered design features that support the safety case and enhance the environmental performance of the facility. These include location selection, use of reinforced pre-cast concrete vaults; a robust hydraulic drainage system; use of steel waste canisters for waste disposal; the facility monitoring system; facility layout; and crediting waste forms. The facility performance assessment (PA) [2] developed to meet the requirements of DOE Order 435.1 “Radioactive Waste Management” credits each of these protective features. Releases from waste forms disposed of at this facility are limited by corrosion of the steel waste canisters which will ultimately allow contact with infiltrating water followed by transport of radionuclides from the vault system. The steel waste canisters were credited for their ability to limit water contact with the waste based on the demonstrated ability of the reinforced pre-caste concrete vaults to provide long-term structural protection of the steel waste canisters. Verification of hydraulic and concrete performance was conducted through laboratory data, field infiltration tests supported by a robust monitoring system, and numerical modeling. Releases into the vault system from activated metals are based on site-specific corrosion data. Radionuclide transport from the vault system from all waste forms is based on site-specific climatological, hydrologic, and stratigraphic data. At INL, the groundwater pathway historically and appropriately has received the most attention. By crediting aspects of the natural system, the engineered vault system, and the waste, estimated radiologic doses via the groundwater pathway are minimal. Air pathway doses were reduced by differentially crediting corrosion of aluminum and stainless steel activated metals resulting in the pathway being screened out of the PA. Groundwater and inadvertent intruder doses were reduced through selective facility layout. This paper provides an overview of the system-wide protective features incorporated into the facility design along with an extensive reference list to supporting technical papers and analyses that provide data and interpretation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Development of a Computer-based Benchmarking and Analytical Tool: Benchmarking and Energy & Water Savings Tool in Dairy Plants (BEST-Dairy) (Final Report)

The overall goal of the project is to develop a computer-based benchmarking and energy and water savings tool (BEST-Dairy) for use in the California dairy industry - including four dairy processes - cheese, fluid milk, butter, and milk powder. BEST-Dairy tool developed in this project provides three options for the user to benchmark each of the dairy product included in the tool, with each option differentiated based on specific detail level of process or plant, i.e., 1) plant level; 2) process-group level, and 3) process-step level. For each detail level, the tool accounts for differences in production and other variables affecting energy use in dairy processes. The dairy products include cheese, fluid milk, butter, milk powder, etc. The BEST-Dairy tool can be applied to a wide range of dairy facilities to provide energy and water savings estimates, which are based upon the comparisons with the best available reference cases that were established through reviewing information from international and national samples. We have performed and completed alpha- and beta-testing (field testing) of the BEST-Dairy tool, through which feedback from voluntary users in the U.S. dairy industry was gathered to validate and improve the tool's functionality. BEST-Dairy v1.2 was formally published in May 2011, and has been made available for free downloads from the internet (i.e., http://best-dairy.lbl.gov). A user's manual has been developed and published as the companion documentation for use with the BEST-Dairy tool. In addition, we also carried out technology transfer activities by engaging the dairy industry in the process of tool development and testing, including field testing, technical presentations, and technical assistance throughout the project. To date, users from more than ten countries in addition to those in the U.S. have downloaded the BEST-Dairy from the LBNL website. It is expected that the use of BEST-Dairy tool will advance understanding of energy and water usage in individual dairy plants, augment benchmarking activities in the market places, and facilitate implementation of efficiency measures and strategies to save energy and water usage in the dairy industry. Industrial adoption of this emerging tool and technology in the market is expected to benefit dairy plants, which are important customers of California utilities. Further demonstration of this benchmarking tool is recommended, for facilitating its commercialization and expansion in functions of the tool. Wider use of this BEST-Dairy tool and its continuous expansion (in functionality) will help to reduce the actual consumption of energy and water in the dairy industry sector. The outcomes comply very well with the goals set by the AB 1250 for PIER program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗
DOE OSTI2015

Response Time Analysis and Test of Protection System Instrument Channels for APR1400 and OPR1000

Safety limits are required to maintain the integrity of physical barriers designed to prevent the uncontrolled release of radioactive materials in nuclear power plants. The safety analysis establishes two critical constraints that include an analytical limit in terms of a measured or calculated variable, and a specific time after the analytical limit is reached to begin protective action. Keeping with the nuclear regulations and industry standards, satisfying these two requirements will ensure that the safety limit will not be exceeded during the design basis event, either an anticipated operational occurrence or a postulated accident. Various studies on the setpoint determination methodology for the safety-related instrumentation have been actively performed to ensure that the requirement of the analytical limit is satisfied. In particular, the protection setpoint methodology for the advanced power reactor 1400 (APP1400) and the optimized power reactor 1000 (OPR1000) has been recently developed to cover both the design basis event and the beyond design basis event. The developed setpoint methodology has also been quantitatively validated using specific computer programs and setpoint calculations. However, the safety of nuclear power plants cannot be fully guaranteed by satisfying the requirement of the analytical limit. In spite of the response time verification requirements of nuclear regulations and industry standards, it is hard to find the studies on the systematically integrated methodology regarding the response time evaluation. In cases of APR1400 and OPR1000, the response time analysis for the plant protection system is partially included in the setpoint calculation and the response time test is separately performed via the specific plant procedure. The test technique has a drawback which is the difficulty to demonstrate completeness of timing test. The analysis technique has also a demerit of resulting in extreme times that not actually possible. Thus, the establishment of the systematic response time evaluation methodology is needed to justify the conformance to the response time requirement used in the safety analysis. This paper proposes the response time evaluation methodology for APR1400 and OPR1000 using the combined analysis and test technique to confirm that the plant protection system can meet the analytical response time assumed in the safety analysis. In addition, the results of the quantitative evaluation performed for APR1400 and OPR1000 are presented in this paper. The proposed response time analysis technique consists of defining the response time requirement, determining the critical signal path for the trip parameter, allocating individual response time to each component on the signal path, and analyzing the total response time for the trip parameter, and demonstrates that the total analyzed response time does not exceed the response time requirement. The proposed response time test technique is composed of defining the response time requirement, determining the critical signal path for the trip parameter, determining the test method for each component on the signal path, performing the response time test, and demonstrates that the total test result does not exceed the response time requirement. The total response time should be tested in a single test that covers from the sensor to the final actuation device on the instrument channel. When the total channel is not tested in a single test, separate tests on groups of components or single components including the total instrument channel shall be combined to verify the total channel response. For APR1400 and OPR1000, the ramp test technique is used for the pressure and differential pressure transmitters and the step function testing technique is applied to the signal processing equipment and final actuation device. As a result, it can be demonstrated that the response time requirement is satisfied by the combined analysis and test technique. Therefore, the proposed methodology in this paper plays a crucial role in guaranteeing the safety of the nuclear power plants systematically satisfying one of two critical requirements from the safety analysis. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗